Overview

Brought to you by YData

Dataset statistics

Number of variables19
Number of observations100090
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.5 MiB
Average record size in memory152.0 B

Variable types

Text7
DateTime1
Categorical1
Numeric10

Alerts

Rating is highly imbalanced (61.7%) Imbalance
Helpfulness is highly skewed (γ1 = 37.68498276) Skewed
Helpfulness has 91665 (91.6%) zeros Zeros

Reproduction

Analysis started2025-01-14 13:58:08.535869
Analysis finished2025-01-14 13:58:41.476488
Duration32.94 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

Distinct100087
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:42.167356image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length9827
Median length3044
Mean length247.31084
Min length9

Characters and Unicode

Total characters24753342
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100084 ?
Unique (%)> 99.9%

Sample

1st rowI enjoyed both The Martian and Artemis so I preordered this one and started it immediately It did not disappoint Andy Weir is one of my favorite authors and Ray Porter is one of my favorite narrators so this combination is a winwin The narration is superb and the writing is great I recommend this book Dont over think it This is worth the price of admissionDisclaimer My enjoyment of the narrator is based on my listening speed I only leave 5 stars for books Ive listened to or will listen to multiple times
2nd rowAwesome story telling Great build up of the characters and universe Cant compare to The Martian as that was novelunique, but this absolutely crushes Artemis Reminds me of a cross between Old Mans War and the Three Body Problem but slightly less cerebral than the latter
3rd rowLet me start off by saying that I strongly enjoyed The Martian and Artemis please, please dont let the negative comments of others dissuade you from reading Artemis Until yesterday, American Gods was my unrivaled favorite as of finishing Project Hail Mary, it is now tied for my very favorite I will not provide spoilers, but if you enjoy good science fiction Scalzi, Taylor, Adams and understand that what makes good science fiction is good science, get Project Hail MaryAs for Ray Porter, I fell in love with his narration of We Are Legion We Are Bob and its sequels His enthusiastic, geeky, humorous, witty, and sarcastic tones are an absolute delight to my ears No other narrator could have done as well or betterI dont regret preordering both the audiobook and a signed copy of Project Hail Mary in the slightest To the contrary, I am elated and am looking forward to listening to this audiobook many, many times
4th rowEvery once in a while Ill finish a book and cant help but get a bit depressed Knowing that the magic and intrigue you felt can never quite be captured again Part of this comes from completing it so quickly, I just couldnt put it down The other was I KNEW I would love it just because it was written by Andy Weir Most books it takes a few chapters to start getting into it but was hooked from the startWithout giving anything away Id say that its a mix of the Bobiverse and the Martian The amazing adventure that comes with space while geeking out on science projects
5th rowIn the Martian his high school science lecture content was acceptable because of the suspense Here, which as far as I can tell is an attempt to recreate that, it totally fails After several hours of boring basic science and NOTHING at all happening, I had enough Its just dull, the attempt at suspense seems manufactured and theres no action I really liked Artemis, and wish hes written a sequel to that I am returning this one disappointed
ValueCountFrequency (%)
the 233344
 
5.2%
and 155291
 
3.4%
i 141305
 
3.1%
to 132311
 
2.9%
a 117343
 
2.6%
of 100599
 
2.2%
this 90405
 
2.0%
it 85428
 
1.9%
is 68450
 
1.5%
book 66648
 
1.5%
Other values (70694) 3336194
73.7%
2025-01-14T22:58:43.022271image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4497685
18.2%
e 2314234
 
9.3%
t 1856343
 
7.5%
o 1623132
 
6.6%
a 1559287
 
6.3%
i 1414888
 
5.7%
n 1334949
 
5.4%
s 1230181
 
5.0%
r 1180807
 
4.8%
h 985183
 
4.0%
Other values (58) 6756653
27.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24753342
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4497685
18.2%
e 2314234
 
9.3%
t 1856343
 
7.5%
o 1623132
 
6.6%
a 1559287
 
6.3%
i 1414888
 
5.7%
n 1334949
 
5.4%
s 1230181
 
5.0%
r 1180807
 
4.8%
h 985183
 
4.0%
Other values (58) 6756653
27.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24753342
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4497685
18.2%
e 2314234
 
9.3%
t 1856343
 
7.5%
o 1623132
 
6.6%
a 1559287
 
6.3%
i 1414888
 
5.7%
n 1334949
 
5.4%
s 1230181
 
5.0%
r 1180807
 
4.8%
h 985183
 
4.0%
Other values (58) 6756653
27.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24753342
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4497685
18.2%
e 2314234
 
9.3%
t 1856343
 
7.5%
o 1623132
 
6.6%
a 1559287
 
6.3%
i 1414888
 
5.7%
n 1334949
 
5.4%
s 1230181
 
5.0%
r 1180807
 
4.8%
h 985183
 
4.0%
Other values (58) 6756653
27.3%
Distinct5319
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
Minimum2002-12-19 00:00:00
Maximum2024-12-04 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-01-14T22:58:43.178806image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:43.319401image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Rating
Categorical

Imbalance 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
5
83790 
4
10110 
3
 
3038
1
 
1633
2
 
1519

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters100090
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row4

Common Values

ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Length

2025-01-14T22:58:43.497727image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-14T22:58:43.677877image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Most occurring characters

ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 100090
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 100090
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 100090
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Average_Rating
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.649985
Minimum4
Maximum4.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:43.840149image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4.3
Q14.6
median4.7
Q34.8
95-th percentile4.9
Maximum4.9
Range0.9
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.1888161
Coefficient of variation (CV)0.040605744
Kurtosis0.56831933
Mean4.649985
Median Absolute Deviation (MAD)0.1
Skewness-0.81639395
Sum465417
Variance0.03565152
MonotonicityNot monotonic
2025-01-14T22:58:44.011192image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4.6 22809
22.8%
4.7 20961
20.9%
4.8 18423
18.4%
4.9 14772
14.8%
4.4 8096
 
8.1%
4.5 7369
 
7.4%
4.3 4603
 
4.6%
4.2 1408
 
1.4%
4 846
 
0.8%
4.1 803
 
0.8%
ValueCountFrequency (%)
4 846
 
0.8%
4.1 803
 
0.8%
4.2 1408
 
1.4%
4.3 4603
 
4.6%
4.4 8096
 
8.1%
4.5 7369
 
7.4%
4.6 22809
22.8%
4.7 20961
20.9%
4.8 18423
18.4%
4.9 14772
14.8%
ValueCountFrequency (%)
4.9 14772
14.8%
4.8 18423
18.4%
4.7 20961
20.9%
4.6 22809
22.8%
4.5 7369
 
7.4%
4.4 8096
 
8.1%
4.3 4603
 
4.6%
4.2 1408
 
1.4%
4.1 803
 
0.8%
4 846
 
0.8%

Num_of_Ratings
Real number (ℝ)

Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44889.823
Minimum98
Maximum215239
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:44.201189image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum98
5-th percentile5126
Q113701
median26734
Q352781
95-th percentile182379
Maximum215239
Range215141
Interquartile range (IQR)39080

Descriptive statistics

Standard deviation50348.856
Coefficient of variation (CV)1.1216096
Kurtosis3.9449164
Mean44889.823
Median Absolute Deviation (MAD)15281
Skewness2.1661403
Sum4.4930224 × 109
Variance2.5350073 × 109
MonotonicityNot monotonic
2025-01-14T22:58:44.399052image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182379 1803
 
1.8%
54757 1739
 
1.7%
36116 1723
 
1.7%
52781 1678
 
1.7%
15885 1653
 
1.7%
45875 1648
 
1.6%
181868 1646
 
1.6%
32619 1630
 
1.6%
101379 1629
 
1.6%
36876 1627
 
1.6%
Other values (90) 83314
83.2%
ValueCountFrequency (%)
98 23
 
< 0.1%
101 26
 
< 0.1%
138 43
< 0.1%
180 33
 
< 0.1%
243 77
0.1%
463 58
0.1%
561 68
0.1%
1031 75
0.1%
1033 100
0.1%
1042 89
0.1%
ValueCountFrequency (%)
215239 1575
1.6%
202151 1600
1.6%
196712 1578
1.6%
182379 1803
1.8%
181868 1646
1.6%
104740 1538
1.5%
101379 1629
1.6%
89067 1582
1.6%
79190 1381
1.4%
62022 1598
1.6%

Helpfulness
Real number (ℝ)

Skewed  Zeros 

Distinct178
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.60107903
Minimum0
Maximum656
Zeros91665
Zeros (%)91.6%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:44.592676image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum656
Range656
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.5868327
Coefficient of variation (CV)14.285697
Kurtosis1960.1281
Mean0.60107903
Median Absolute Deviation (MAD)0
Skewness37.684983
Sum60162
Variance73.733696
MonotonicityNot monotonic
2025-01-14T22:58:44.796448image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 91665
91.6%
1 4964
 
5.0%
2 1182
 
1.2%
3 550
 
0.5%
4 314
 
0.3%
5 161
 
0.2%
6 124
 
0.1%
7 96
 
0.1%
8 84
 
0.1%
9 60
 
0.1%
Other values (168) 890
 
0.9%
ValueCountFrequency (%)
0 91665
91.6%
1 4964
 
5.0%
2 1182
 
1.2%
3 550
 
0.5%
4 314
 
0.3%
5 161
 
0.2%
6 124
 
0.1%
7 96
 
0.1%
8 84
 
0.1%
9 60
 
0.1%
ValueCountFrequency (%)
656 1
< 0.1%
640 1
< 0.1%
597 1
< 0.1%
596 1
< 0.1%
467 1
< 0.1%
456 1
< 0.1%
452 1
< 0.1%
445 1
< 0.1%
438 1
< 0.1%
429 1
< 0.1%
Distinct63245
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:45.772504image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length758
Median length142
Mean length10.108083
Min length1

Characters and Unicode

Total characters1011718
Distinct characters268
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55705 ?
Unique (%)55.7%

Sample

1st rowDavidgonzalezsr
2nd rowDavid
3rd rowRoswatheist
4th rowJ. Kenney
5th rowCelia
ValueCountFrequency (%)
customer 6471
 
3.9%
amazon 5285
 
3.2%
anonymous 3914
 
2.3%
user 3865
 
2.3%
m 1588
 
1.0%
a 1378
 
0.8%
j 1324
 
0.8%
s 1197
 
0.7%
kindle 1196
 
0.7%
c 1136
 
0.7%
Other values (41911) 139759
83.6%
2025-01-14T22:58:46.990902image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 90784
 
9.0%
a 85561
 
8.5%
n 71118
 
7.0%
67155
 
6.6%
r 62900
 
6.2%
o 59364
 
5.9%
i 54228
 
5.4%
s 46081
 
4.6%
l 41373
 
4.1%
t 35585
 
3.5%
Other values (258) 397569
39.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1011718
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 90784
 
9.0%
a 85561
 
8.5%
n 71118
 
7.0%
67155
 
6.6%
r 62900
 
6.2%
o 59364
 
5.9%
i 54228
 
5.4%
s 46081
 
4.6%
l 41373
 
4.1%
t 35585
 
3.5%
Other values (258) 397569
39.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1011718
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 90784
 
9.0%
a 85561
 
8.5%
n 71118
 
7.0%
67155
 
6.6%
r 62900
 
6.2%
o 59364
 
5.9%
i 54228
 
5.4%
s 46081
 
4.6%
l 41373
 
4.1%
t 35585
 
3.5%
Other values (258) 397569
39.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1011718
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 90784
 
9.0%
a 85561
 
8.5%
n 71118
 
7.0%
67155
 
6.6%
r 62900
 
6.2%
o 59364
 
5.9%
i 54228
 
5.4%
s 46081
 
4.6%
l 41373
 
4.1%
t 35585
 
3.5%
Other values (258) 397569
39.3%
Distinct63153
Distinct (%)63.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:47.916955image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length128
Median length115
Mean length21.540603
Min length1

Characters and Unicode

Total characters2155999
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57934 ?
Unique (%)57.9%

Sample

1st rowBazinga
2nd rowAbsolutely Great way better than Artemis
3rd rowHighest Order of Geekgasm Medal
4th rowSo good, its depressing
5th rowNOT the Martian
ValueCountFrequency (%)
a 12243
 
3.3%
the 10523
 
2.9%
book 9450
 
2.6%
story 9427
 
2.6%
and 9103
 
2.5%
great 8956
 
2.4%
of 6214
 
1.7%
it 5913
 
1.6%
this 5607
 
1.5%
to 5511
 
1.5%
Other values (13802) 285690
77.5%
2025-01-14T22:58:49.397367image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
272693
 
12.6%
e 200659
 
9.3%
t 158261
 
7.3%
o 147440
 
6.8%
a 135604
 
6.3%
i 130735
 
6.1%
n 129283
 
6.0%
r 120945
 
5.6%
s 91733
 
4.3%
l 84558
 
3.9%
Other values (54) 684088
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2155999
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
272693
 
12.6%
e 200659
 
9.3%
t 158261
 
7.3%
o 147440
 
6.8%
a 135604
 
6.3%
i 130735
 
6.1%
n 129283
 
6.0%
r 120945
 
5.6%
s 91733
 
4.3%
l 84558
 
3.9%
Other values (54) 684088
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2155999
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
272693
 
12.6%
e 200659
 
9.3%
t 158261
 
7.3%
o 147440
 
6.8%
a 135604
 
6.3%
i 130735
 
6.1%
n 129283
 
6.0%
r 120945
 
5.6%
s 91733
 
4.3%
l 84558
 
3.9%
Other values (54) 684088
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2155999
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
272693
 
12.6%
e 200659
 
9.3%
t 158261
 
7.3%
o 147440
 
6.8%
a 135604
 
6.3%
i 130735
 
6.1%
n 129283
 
6.0%
r 120945
 
5.6%
s 91733
 
4.3%
l 84558
 
3.9%
Other values (54) 684088
31.7%

Link
Text

Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:49.908253image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length104
Median length80
Mean length65.561704
Min length50

Characters and Unicode

Total characters6562071
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
2nd rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
3rd rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
4th rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
5th rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
ValueCountFrequency (%)
https://www.audible.com/pd/project-hail-mary-audiobook/b08g9prs1k 1803
 
1.8%
https://www.audible.com/pd/circe-audiobook/b0794bxzbf 1739
 
1.7%
https://www.audible.com/pd/the-handmaids-tale-special-edition-audiobook/b06xfw9yz5 1723
 
1.7%
https://www.audible.com/pd/the-sandman-audiobook/b086wp794z 1678
 
1.7%
https://www.audible.com/pd/the-mystwick-school-of-musicraft-audiobook/b07mt4mtgp 1653
 
1.7%
https://www.audible.com/pd/the-hate-u-give-audiobook/b01nagd7tv 1648
 
1.6%
https://www.audible.com/pd/becoming-audiobook/b07b3bcz9s 1646
 
1.6%
https://www.audible.com/pd/evil-eye-audiobook/b07qp1x8b7 1630
 
1.6%
https://www.audible.com/pd/the-nightingale-audiobook/b00nybqkfq 1629
 
1.6%
https://www.audible.com/pd/kitchen-confidential-audiobook/b002va8gsa 1627
 
1.6%
Other values (90) 83314
83.2%
2025-01-14T22:58:50.583032image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 500450
 
7.6%
o 491236
 
7.5%
d 349712
 
5.3%
- 326860
 
5.0%
i 312280
 
4.8%
w 309080
 
4.7%
e 296420
 
4.5%
t 285896
 
4.4%
u 227886
 
3.5%
b 214375
 
3.3%
Other values (55) 3247876
49.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6562071
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 500450
 
7.6%
o 491236
 
7.5%
d 349712
 
5.3%
- 326860
 
5.0%
i 312280
 
4.8%
w 309080
 
4.7%
e 296420
 
4.5%
t 285896
 
4.4%
u 227886
 
3.5%
b 214375
 
3.3%
Other values (55) 3247876
49.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6562071
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 500450
 
7.6%
o 491236
 
7.5%
d 349712
 
5.3%
- 326860
 
5.0%
i 312280
 
4.8%
w 309080
 
4.7%
e 296420
 
4.5%
t 285896
 
4.4%
u 227886
 
3.5%
b 214375
 
3.3%
Other values (55) 3247876
49.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6562071
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 500450
 
7.6%
o 491236
 
7.5%
d 349712
 
5.3%
- 326860
 
5.0%
i 312280
 
4.8%
w 309080
 
4.7%
e 296420
 
4.5%
t 285896
 
4.4%
u 227886
 
3.5%
b 214375
 
3.3%
Other values (55) 3247876
49.5%
Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:51.046746image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length27
Median length25
Mean length22.381287
Min length10

Characters and Unicode

Total characters2240143
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row162833,15895,2619,672,360
2nd row162833,15895,2619,672,360
3rd row162833,15895,2619,672,360
4th row162833,15895,2619,672,360
5th row162833,15895,2619,672,360
ValueCountFrequency (%)
162833,15895,2619,672,360 1803
 
1.8%
42989,8803,2159,494,312 1739
 
1.7%
24398,7248,2683,1000,787 1723
 
1.7%
41741,6347,2482,1077,1134 1678
 
1.7%
12241,2785,628,123,108 1653
 
1.7%
38215,5922,1240,276,222 1648
 
1.6%
167358,11293,2099,526,592 1646
 
1.6%
21973,7120,2395,652,479 1630
 
1.6%
88056,10560,1913,488,362 1629
 
1.6%
30168,5163,1181,203,161 1627
 
1.6%
Other values (90) 83314
83.2%
2025-01-14T22:58:51.731826image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 400360
17.9%
1 293283
13.1%
2 235603
10.5%
3 197365
8.8%
4 194297
8.7%
6 180444
8.1%
5 159101
 
7.1%
8 158986
 
7.1%
9 143216
 
6.4%
7 140322
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2240143
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
, 400360
17.9%
1 293283
13.1%
2 235603
10.5%
3 197365
8.8%
4 194297
8.7%
6 180444
8.1%
5 159101
 
7.1%
8 158986
 
7.1%
9 143216
 
6.4%
7 140322
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2240143
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
, 400360
17.9%
1 293283
13.1%
2 235603
10.5%
3 197365
8.8%
4 194297
8.7%
6 180444
8.1%
5 159101
 
7.1%
8 158986
 
7.1%
9 143216
 
6.4%
7 140322
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2240143
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
, 400360
17.9%
1 293283
13.1%
2 235603
10.5%
3 197365
8.8%
4 194297
8.7%
6 180444
8.1%
5 159101
 
7.1%
8 158986
 
7.1%
9 143216
 
6.4%
7 140322
 
6.3%
Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:52.393052image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.234129
Min length10

Characters and Unicode

Total characters2125324
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row156733,7989,1298,287,227
2nd row156733,7989,1298,287,227
3rd row156733,7989,1298,287,227
4th row156733,7989,1298,287,227
5th row156733,7989,1298,287,227
ValueCountFrequency (%)
156733,7989,1298,287,227 1803
 
1.8%
43762,4431,816,203,134 1739
 
1.7%
24729,5316,1623,518,402 1723
 
1.7%
41992,2633,727,328,483 1678
 
1.7%
12353,1605,321,55,61 1653
 
1.7%
36667,3855,831,145,134 1648
 
1.6%
150764,8445,1619,378,412 1646
 
1.6%
24192,3973,1106,296,275 1630
 
1.6%
79759,9539,1759,409,288 1629
 
1.6%
26805,3001,736,128,75 1627
 
1.6%
Other values (90) 83314
83.2%
2025-01-14T22:58:53.132603image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 400360
18.8%
1 267664
12.6%
2 229020
10.8%
3 185731
8.7%
5 168791
7.9%
6 159705
 
7.5%
4 152021
 
7.2%
7 145325
 
6.8%
8 144417
 
6.8%
0 141208
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2125324
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
, 400360
18.8%
1 267664
12.6%
2 229020
10.8%
3 185731
8.7%
5 168791
7.9%
6 159705
 
7.5%
4 152021
 
7.2%
7 145325
 
6.8%
8 144417
 
6.8%
0 141208
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2125324
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
, 400360
18.8%
1 267664
12.6%
2 229020
10.8%
3 185731
8.7%
5 168791
7.9%
6 159705
 
7.5%
4 152021
 
7.2%
7 145325
 
6.8%
8 144417
 
6.8%
0 141208
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2125324
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
, 400360
18.8%
1 267664
12.6%
2 229020
10.8%
3 185731
8.7%
5 168791
7.9%
6 159705
 
7.5%
4 152021
 
7.2%
7 145325
 
6.8%
8 144417
 
6.8%
0 141208
 
6.6%
Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:53.672346image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length26
Median length24
Mean length22.147257
Min length10

Characters and Unicode

Total characters2216719
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row145112,16872,2818,763,416
2nd row145112,16872,2818,763,416
3rd row145112,16872,2818,763,416
4th row145112,16872,2818,763,416
5th row145112,16872,2818,763,416
ValueCountFrequency (%)
145112,16872,2818,763,416 1803
 
1.8%
37805,8286,2189,532,302 1739
 
1.7%
21863,6313,2504,957,853 1723
 
1.7%
35483,5976,2420,1029,1076 1678
 
1.7%
10595,2743,765,147,92 1653
 
1.7%
34350,5452,1234,255,189 1648
 
1.6%
146729,11086,1957,499,466 1646
 
1.6%
19324,6598,2562,726,499 1630
 
1.6%
79872,9093,1753,489,325 1629
 
1.6%
25132,4213,975,162,95 1627
 
1.6%
Other values (90) 83314
83.2%
2025-01-14T22:58:54.512161image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 400360
18.1%
1 294153
13.3%
2 245146
11.1%
3 193262
8.7%
5 190961
8.6%
6 166979
7.5%
4 165851
7.5%
7 157768
 
7.1%
8 146072
 
6.6%
9 128681
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2216719
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
, 400360
18.1%
1 294153
13.3%
2 245146
11.1%
3 193262
8.7%
5 190961
8.6%
6 166979
7.5%
4 165851
7.5%
7 157768
 
7.1%
8 146072
 
6.6%
9 128681
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2216719
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
, 400360
18.1%
1 294153
13.3%
2 245146
11.1%
3 193262
8.7%
5 190961
8.6%
6 166979
7.5%
4 165851
7.5%
7 157768
 
7.1%
8 146072
 
6.6%
9 128681
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2216719
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
, 400360
18.1%
1 294153
13.3%
2 245146
11.1%
3 193262
8.7%
5 190961
8.6%
6 166979
7.5%
4 165851
7.5%
7 157768
 
7.1%
8 146072
 
6.6%
9 128681
 
5.8%

depth
Real number (ℝ)

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-38.258577
Minimum-100
Maximum-7.1523003
Zeros0
Zeros (%)0.0%
Negative100090
Negative (%)100.0%
Memory size782.1 KiB
2025-01-14T22:58:54.750007image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile-64.759476
Q1-47.155024
median-43.939172
Q3-27.624641
95-th percentile-10.608418
Maximum-7.1523003
Range92.8477
Interquartile range (IQR)19.530383

Descriptive statistics

Standard deviation18.946355
Coefficient of variation (CV)-0.49521849
Kurtosis-0.5987681
Mean-38.258577
Median Absolute Deviation (MAD)15.638057
Skewness-0.27822933
Sum-3829301
Variance358.96436
MonotonicityNot monotonic
2025-01-14T22:58:54.953538image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-100 68
 
0.1%
-80.89406021 4
 
< 0.1%
-81.00632235 4
 
< 0.1%
-45.59546089 4
 
< 0.1%
-45.71369347 3
 
< 0.1%
-47.81311269 3
 
< 0.1%
-63.72478405 3
 
< 0.1%
-62.15893812 3
 
< 0.1%
-28.84917266 3
 
< 0.1%
-62.23075305 3
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
-100 68
0.1%
-82.78937872 1
 
< 0.1%
-81.99859719 1
 
< 0.1%
-81.96753379 1
 
< 0.1%
-81.94306718 1
 
< 0.1%
-81.93390447 1
 
< 0.1%
-81.92098004 1
 
< 0.1%
-81.91679663 1
 
< 0.1%
-81.91339063 1
 
< 0.1%
-81.90049767 1
 
< 0.1%
ValueCountFrequency (%)
-7.152300319 1
< 0.1%
-7.304030463 1
< 0.1%
-7.423963903 1
< 0.1%
-7.44937313 1
< 0.1%
-7.488854866 1
< 0.1%
-7.504674715 1
< 0.1%
-7.514498995 1
< 0.1%
-7.52113178 1
< 0.1%
-7.56997945 1
< 0.1%
-7.613268058 1
< 0.1%

breadth
Real number (ℝ)

Distinct96272
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.93689153
Minimum0.00078800238
Maximum3.448727
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:55.159772image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum0.00078800238
5-th percentile0.22336455
Q10.49856735
median0.84506302
Q31.296656
95-th percentile1.8907354
Maximum3.448727
Range3.447939
Interquartile range (IQR)0.79808862

Descriptive statistics

Standard deviation0.54597811
Coefficient of variation (CV)0.58275488
Kurtosis0.4594521
Mean0.93689153
Median Absolute Deviation (MAD)0.38863205
Skewness0.77663022
Sum93773.473
Variance0.2980921
MonotonicityNot monotonic
2025-01-14T22:58:55.356107image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.530851483 2082
 
2.1%
1.890735406 1383
 
1.4%
2.417348688 213
 
0.2%
0.1846197013 68
 
0.1%
3.448727027 29
 
< 0.1%
3.245076312 18
 
< 0.1%
1.726449479 4
 
< 0.1%
0.2947324003 3
 
< 0.1%
0.6518817938 3
 
< 0.1%
0.7065778109 3
 
< 0.1%
Other values (96262) 96284
96.2%
ValueCountFrequency (%)
0.0007880023768 1
< 0.1%
0.003001233725 1
< 0.1%
0.004244478114 1
< 0.1%
0.005104945696 1
< 0.1%
0.005305920743 1
< 0.1%
0.005556320068 1
< 0.1%
0.006765129257 1
< 0.1%
0.006804829836 1
< 0.1%
0.007886365789 1
< 0.1%
0.008546587723 1
< 0.1%
ValueCountFrequency (%)
3.448727027 29
< 0.1%
3.44778801 1
 
< 0.1%
3.441408737 1
 
< 0.1%
3.435680628 1
 
< 0.1%
3.435662837 1
 
< 0.1%
3.427389886 1
 
< 0.1%
3.413356644 1
 
< 0.1%
3.40900809 1
 
< 0.1%
3.408528499 1
 
< 0.1%
3.402229271 1
 
< 0.1%

Topic_1
Real number (ℝ)

Distinct98605
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.26966956
Minimum3.6520698 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:55.565307image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum3.6520698 × 10-20
5-th percentile1.371576 × 10-19
Q10.059552751
median0.21361214
Q30.39506786
95-th percentile0.82198083
Maximum1
Range1
Interquartile range (IQR)0.33551511

Descriptive statistics

Standard deviation0.25275045
Coefficient of variation (CV)0.93725984
Kurtosis0.54502948
Mean0.26966956
Median Absolute Deviation (MAD)0.16433487
Skewness1.0674405
Sum26991.226
Variance0.063882789
MonotonicityNot monotonic
2025-01-14T22:58:55.769515image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1384
 
1.4%
0.2 68
 
0.1%
0.01923969365 4
 
< 0.1%
7.835382574 × 10-204
 
< 0.1%
0.4869127457 3
 
< 0.1%
0.2840498678 3
 
< 0.1%
0.2471973339 3
 
< 0.1%
0.2043033164 3
 
< 0.1%
1.138469075 × 10-183
 
< 0.1%
0.748100819 3
 
< 0.1%
Other values (98595) 98612
98.5%
ValueCountFrequency (%)
3.652069822 × 10-201
< 0.1%
4.03012295 × 10-201
< 0.1%
4.234286932 × 10-201
< 0.1%
4.324581946 × 10-201
< 0.1%
4.373963289 × 10-201
< 0.1%
4.374970462 × 10-201
< 0.1%
4.427322521 × 10-201
< 0.1%
4.444616811 × 10-201
< 0.1%
4.49903154 × 10-201
< 0.1%
4.531071584 × 10-201
< 0.1%
ValueCountFrequency (%)
1 1384
1.4%
0.9999734999 1
 
< 0.1%
0.9999654788 1
 
< 0.1%
0.999957446 1
 
< 0.1%
0.9998721228 1
 
< 0.1%
0.9998483736 1
 
< 0.1%
0.9997853276 1
 
< 0.1%
0.9997742381 1
 
< 0.1%
0.9996149559 1
 
< 0.1%
0.9995344523 1
 
< 0.1%

Topic_2
Real number (ℝ)

Distinct97904
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.34607305
Minimum3.9022577 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:55.981977image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum3.9022577 × 10-20
5-th percentile1.4140892 × 10-19
Q10.093793319
median0.29854413
Q30.53950227
95-th percentile0.92960006
Maximum1
Range1
Interquartile range (IQR)0.44570895

Descriptive statistics

Standard deviation0.28861145
Coefficient of variation (CV)0.83396108
Kurtosis-0.59528849
Mean0.34607305
Median Absolute Deviation (MAD)0.21938602
Skewness0.61878375
Sum34638.452
Variance0.083296571
MonotonicityNot monotonic
2025-01-14T22:58:56.214270image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2082
 
2.1%
0.2 68
 
0.1%
1.014664218 × 10-194
 
< 0.1%
0.09726404677 4
 
< 0.1%
0.5727192809 3
 
< 0.1%
0.5130872543 3
 
< 0.1%
5.180021046 × 10-203
 
< 0.1%
0.515082537 3
 
< 0.1%
1.375751387 × 10-193
 
< 0.1%
5.881867077 × 10-203
 
< 0.1%
Other values (97894) 97914
97.8%
ValueCountFrequency (%)
3.90225773 × 10-201
< 0.1%
4.227633998 × 10-201
< 0.1%
4.279855649 × 10-201
< 0.1%
4.297283985 × 10-201
< 0.1%
4.374970462 × 10-201
< 0.1%
4.554657809 × 10-201
< 0.1%
4.564498996 × 10-201
< 0.1%
4.565971991 × 10-201
< 0.1%
4.579445462 × 10-201
< 0.1%
4.626093779 × 10-201
< 0.1%
ValueCountFrequency (%)
1 2082
2.1%
0.9999915169 1
 
< 0.1%
0.999988786 1
 
< 0.1%
0.9999538756 1
 
< 0.1%
0.9999534492 1
 
< 0.1%
0.9999356386 1
 
< 0.1%
0.9999182809 1
 
< 0.1%
0.9999127713 1
 
< 0.1%
0.9999087417 1
 
< 0.1%
0.9998902463 1
 
< 0.1%

Topic_3
Real number (ℝ)

Distinct99965
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10547139
Minimum4.3036353 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:56.417835image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum4.3036353 × 10-20
5-th percentile1.2310498 × 10-19
Q12.4302143 × 10-19
median0.0035364273
Q30.11253362
95-th percentile0.5606404
Maximum1
Range1
Interquartile range (IQR)0.11253362

Descriptive statistics

Standard deviation0.18674536
Coefficient of variation (CV)1.7705782
Kurtosis3.6360853
Mean0.10547139
Median Absolute Deviation (MAD)0.0035364273
Skewness2.0781769
Sum10556.632
Variance0.034873828
MonotonicityNot monotonic
2025-01-14T22:58:56.888651image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 68
 
0.1%
1 18
 
< 0.1%
8.668395088 × 10-204
 
< 0.1%
7.835382574 × 10-204
 
< 0.1%
1.014664218 × 10-194
 
< 0.1%
5.881867077 × 10-203
 
< 0.1%
0.221521842 3
 
< 0.1%
3.41496714 × 10-193
 
< 0.1%
3.640937394 × 10-193
 
< 0.1%
0.1360344191 3
 
< 0.1%
Other values (99955) 99977
99.9%
ValueCountFrequency (%)
4.303635283 × 10-201
< 0.1%
4.42855234 × 10-201
< 0.1%
4.444616811 × 10-201
< 0.1%
4.564498996 × 10-201
< 0.1%
4.565971991 × 10-201
< 0.1%
4.579445462 × 10-201
< 0.1%
4.655546473 × 10-201
< 0.1%
4.665002897 × 10-202
< 0.1%
4.69722925 × 10-201
< 0.1%
4.773134742 × 10-201
< 0.1%
ValueCountFrequency (%)
1 18
< 0.1%
0.9994431304 1
 
< 0.1%
0.998564268 1
 
< 0.1%
0.9974149247 1
 
< 0.1%
0.9959817173 1
 
< 0.1%
0.9939915731 1
 
< 0.1%
0.9938396188 1
 
< 0.1%
0.9927391194 1
 
< 0.1%
0.9925274462 1
 
< 0.1%
0.991891142 1
 
< 0.1%

Topic_4
Real number (ℝ)

Distinct99955
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.091586131
Minimum4.297284 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:57.122590image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum4.297284 × 10-20
5-th percentile1.2273917 × 10-19
Q12.3308009 × 10-19
median0.0026684712
Q30.057729029
95-th percentile0.58588725
Maximum1
Range1
Interquartile range (IQR)0.057729029

Descriptive statistics

Standard deviation0.19047832
Coefficient of variation (CV)2.0797726
Kurtosis5.0766486
Mean0.091586131
Median Absolute Deviation (MAD)0.0026684712
Skewness2.4342876
Sum9166.8559
Variance0.036281992
MonotonicityNot monotonic
2025-01-14T22:58:57.340908image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 68
 
0.1%
1 29
 
< 0.1%
1.014664218 × 10-194
 
< 0.1%
7.835382574 × 10-204
 
< 0.1%
8.668395088 × 10-204
 
< 0.1%
5.881867077 × 10-203
 
< 0.1%
0.1776669255 3
 
< 0.1%
5.180021046 × 10-203
 
< 0.1%
1.138469075 × 10-183
 
< 0.1%
1.375751387 × 10-193
 
< 0.1%
Other values (99945) 99966
99.9%
ValueCountFrequency (%)
4.297283985 × 10-201
< 0.1%
4.676107462 × 10-201
< 0.1%
4.878577417 × 10-201
< 0.1%
4.887300455 × 10-201
< 0.1%
4.915874196 × 10-201
< 0.1%
5.048076153 × 10-201
< 0.1%
5.108557687 × 10-201
< 0.1%
5.133490294 × 10-201
< 0.1%
5.145548339 × 10-201
< 0.1%
5.157039521 × 10-201
< 0.1%
ValueCountFrequency (%)
1 29
< 0.1%
0.9999433717 1
 
< 0.1%
0.9994879295 1
 
< 0.1%
0.9989445745 1
 
< 0.1%
0.9989429448 1
 
< 0.1%
0.9983426667 1
 
< 0.1%
0.9966988287 1
 
< 0.1%
0.99666696 1
 
< 0.1%
0.9962246178 1
 
< 0.1%
0.9954662302 1
 
< 0.1%

Topic_5
Real number (ℝ)

Distinct99770
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18719986
Minimum3.6520698 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-14T22:58:57.543015image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum3.6520698 × 10-20
5-th percentile1.2502887 × 10-19
Q13.8765911 × 10-19
median0.085986569
Q30.30882956
95-th percentile0.68028827
Maximum1
Range1
Interquartile range (IQR)0.30882956

Descriptive statistics

Standard deviation0.23135695
Coefficient of variation (CV)1.235882
Kurtosis0.96397104
Mean0.18719986
Median Absolute Deviation (MAD)0.085986569
Skewness1.3243724
Sum18736.834
Variance0.053526038
MonotonicityNot monotonic
2025-01-14T22:58:57.750537image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 213
 
0.2%
0.2 68
 
0.1%
0.8834962596 4
 
< 0.1%
7.835382574 × 10-204
 
< 0.1%
1.014664218 × 10-194
 
< 0.1%
0.2912463 3
 
< 0.1%
0.1029472211 3
 
< 0.1%
3.640937394 × 10-193
 
< 0.1%
0.7159501322 3
 
< 0.1%
0.03037733898 3
 
< 0.1%
Other values (99760) 99782
99.7%
ValueCountFrequency (%)
3.652069822 × 10-201
< 0.1%
4.227633998 × 10-201
< 0.1%
4.279855649 × 10-201
< 0.1%
4.324581946 × 10-201
< 0.1%
4.373963289 × 10-201
< 0.1%
4.49903154 × 10-201
< 0.1%
4.531071584 × 10-201
< 0.1%
4.554268154 × 10-201
< 0.1%
4.56024924 × 10-201
< 0.1%
4.665002897 × 10-202
< 0.1%
ValueCountFrequency (%)
1 213
0.2%
0.9999753856 1
 
< 0.1%
0.9999590094 1
 
< 0.1%
0.9999356111 1
 
< 0.1%
0.9998586022 1
 
< 0.1%
0.9997431163 1
 
< 0.1%
0.9996866809 1
 
< 0.1%
0.9995259639 1
 
< 0.1%
0.9995007141 1
 
< 0.1%
0.9992175566 1
 
< 0.1%

Interactions

2025-01-14T22:58:38.159656image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:22.532772image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:24.098475image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:25.877299image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:27.744617image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:29.450057image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:30.862901image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:32.517869image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:34.563738image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:36.348278image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:38.347722image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:22.709328image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:24.284599image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:26.050297image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:27.905533image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:29.587596image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:30.996296image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:32.696084image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:34.754146image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:36.527327image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:38.518860image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:22.930933image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:24.450176image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:26.253376image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:28.076129image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:29.720014image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:31.138407image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:32.874153image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:34.923348image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:36.709886image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:38.697954image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:23.061774image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:24.612370image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:26.436446image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:28.268564image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:29.871399image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:31.305720image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:33.060064image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:35.102955image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:36.902227image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:38.860242image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:23.197790image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:24.798504image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:26.622274image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:28.443304image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:30.006711image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:31.477616image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:33.531065image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:35.301094image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:37.094510image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:39.052820image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:23.354358image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:24.982234image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:26.805514image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:28.650499image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:30.157927image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:31.648096image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:33.712596image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:35.486882image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:37.292673image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:39.215074image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:23.490125image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:25.179370image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:26.996186image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:28.819990image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:30.297185image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:31.828094image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:33.871317image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:35.651967image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:37.468141image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:39.379869image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:23.640616image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:25.343113image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:27.196768image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:29.059963image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:30.441576image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:32.001801image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:34.054327image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:35.816912image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:37.641082image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:39.559170image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:23.789003image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:25.535390image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:27.401639image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:29.190041image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:30.580774image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:32.177022image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:34.224113image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:36.008193image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:37.792799image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:39.732744image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:23.942542image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:25.710912image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:27.573468image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:29.324241image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:30.722615image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:32.347133image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:34.381987image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:36.174510image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:58:37.966348image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Correlations

2025-01-14T22:58:57.926266image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Average_RatingHelpfulnessNum_of_RatingsRatingTopic_1Topic_2Topic_3Topic_4Topic_5breadthdepth
Average_Rating1.000-0.1030.3320.1920.048-0.1340.0010.0370.0790.0340.017
Helpfulness-0.1031.000-0.0800.0110.0360.020-0.001-0.0340.011-0.0570.022
Num_of_Ratings0.332-0.0801.0000.0860.033-0.0960.0350.0310.0050.0360.036
Rating0.1920.0110.0861.0000.0460.0640.0270.0590.0420.0410.049
Topic_10.0480.0360.0330.0461.000-0.397-0.091-0.057-0.032-0.271-0.075
Topic_2-0.1340.020-0.0960.064-0.3971.000-0.069-0.085-0.306-0.367-0.117
Topic_30.001-0.0010.0350.027-0.091-0.0691.000-0.041-0.139-0.1370.468
Topic_40.037-0.0340.0310.059-0.057-0.085-0.0411.000-0.173-0.0390.416
Topic_50.0790.0110.0050.042-0.032-0.306-0.139-0.1731.000-0.2900.303
breadth0.034-0.0570.0360.041-0.271-0.367-0.137-0.039-0.2901.000-0.487
depth0.0170.0220.0360.049-0.075-0.1170.4680.4160.303-0.4871.000

Missing values

2025-01-14T22:58:40.046625image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-01-14T22:58:40.853987image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Review_TextPosted_DateRatingAverage_RatingNum_of_RatingsHelpfulnessReviewerReview TitleLinkRating_DistributionRating_of_PerformanceRating_of_StorydepthbreadthTopic_1Topic_2Topic_3Topic_4Topic_5
0I enjoyed both The Martian and Artemis so I preordered this one and started it immediately It did not disappoint Andy Weir is one of my favorite authors and Ray Porter is one of my favorite narrators so this combination is a winwin The narration is superb and the writing is great I recommend this book Dont over think it This is worth the price of admissionDisclaimer My enjoyment of the narrator is based on my listening speed I only leave 5 stars for books Ive listened to or will listen to multiple times05-04-2154.9182379656DavidgonzalezsrBazingahttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-9.4243600.4062412.128002e-010.1224372.954639e-013.858786e-023.307113e-01
1Awesome story telling Great build up of the characters and universe Cant compare to The Martian as that was novelunique, but this absolutely crushes Artemis Reminds me of a cross between Old Mans War and the Three Body Problem but slightly less cerebral than the latter05-05-2154.9182379159DavidAbsolutely Great way better than Artemishttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-45.4465051.1684811.822569e-190.4155304.746866e-011.097837e-011.822569e-19
2Let me start off by saying that I strongly enjoyed The Martian and Artemis please, please dont let the negative comments of others dissuade you from reading Artemis Until yesterday, American Gods was my unrivaled favorite as of finishing Project Hail Mary, it is now tied for my very favorite I will not provide spoilers, but if you enjoy good science fiction Scalzi, Taylor, Adams and understand that what makes good science fiction is good science, get Project Hail MaryAs for Ray Porter, I fell in love with his narration of We Are Legion We Are Bob and its sequels His enthusiastic, geeky, humorous, witty, and sarcastic tones are an absolute delight to my ears No other narrator could have done as well or betterI dont regret preordering both the audiobook and a signed copy of Project Hail Mary in the slightest To the contrary, I am elated and am looking forward to listening to this audiobook many, many times05-05-2154.9182379157RoswatheistHighest Order of Geekgasm Medalhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-11.4235090.1130622.995402e-010.4629114.448491e-022.398360e-021.690806e-01
3Every once in a while Ill finish a book and cant help but get a bit depressed Knowing that the magic and intrigue you felt can never quite be captured again Part of this comes from completing it so quickly, I just couldnt put it down The other was I KNEW I would love it just because it was written by Andy Weir Most books it takes a few chapters to start getting into it but was hooked from the startWithout giving anything away Id say that its a mix of the Bobiverse and the Martian The amazing adventure that comes with space while geeking out on science projects05-11-2154.918237934J. KenneySo good, its depressinghttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-45.7262160.3638274.460136e-010.3179322.611982e-192.611982e-192.360541e-01
4In the Martian his high school science lecture content was acceptable because of the suspense Here, which as far as I can tell is an attempt to recreate that, it totally fails After several hours of boring basic science and NOTHING at all happening, I had enough Its just dull, the attempt at suspense seems manufactured and theres no action I really liked Artemis, and wish hes written a sequel to that I am returning this one disappointed05-08-2144.918237920CeliaNOT the Martianhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-46.4317410.3244193.178159e-010.4802674.367078e-194.367078e-192.019173e-01
5I rarely write reviews but had to this time This was the best and most fun Ive had listening to an audiobook ever Perfect mix of science fiction and humor and just overall amazing The narrator is so talented Highly highly highly recommend06-25-2154.918237915EllenWow AMAZE AMAZE AMAZEhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-9.7021930.1948772.540745e-010.1753407.829605e-021.106601e-013.816293e-01
6It has all the science we love from an Andy Weir book It makes you think and even look up stuff you didnt know, but it was a tad predictable If you love his other two books you will enjoy this readlisten Would have like to hear RC Bray as the narrator, the Martian audio book will always be one of my favorites While the narrator wasnt bad in this one, just wasnt sucked into the characters as much as with the Martian or even Artemis Maybe having preorder the book built up a hype He couldnt have possible matched but I did finish the book in three days I would recommend05-12-2144.91823797Robert SchenkSmart but predictablehttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-11.6206760.5772296.875838e-010.1816824.669591e-028.219903e-037.581845e-02
7if you know Andy Weir, this book will fit your expectations while still offering great surprises however, it also shows done of his weakness characters are generally flat, and the protagonists shallow sarcasm wears on you The reader performs it admirably, but the work could have benefited from backing off a bit rather than leaning into the goofinessThe inherently mysterious nature of the work makes it hard to discuss the plot or characters in a review, but suffice it to say that the incredible amount of research and thought that went into the science is on display, and theres some creative thinking there that seems both wondrous and plausible All the moving parts cone together on the end, but not without reasonable yet unexpected consequencesI enjoyed it, but of you arent a fan of Weir, try The Martian first05-12-2144.91823796jellyA fun Weir novel, but a step backhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-13.4106550.5229503.007686e-010.3645843.184089e-013.541382e-041.588456e-02
8OUTSTANDING, JUST ABSOLUTELY OUTSTANDINGThis book will stay in your memories, The main characters will stay in your memories, and you will miss them10-10-2154.91823794Daniel C.TO JOE BISHOP SKIPPY ANDY SAYS,HOLD MY BEERhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-30.8705930.6181454.928029e-010.2845894.386934e-192.209981e-011.609797e-03
9Definately Weir returning to his origins A single engineerscientist against all odds solving problems and making things workIts a good book Though the lack of interest in using the astrophage problem to solve it did become a bit annoying They have a 5000,000 ISP rocket engine and thats never used to deploy anti astrophage methods makes no senseThis does suffer from the Portal 2 dillema Is it as good as the Martian No Is it good Yes Below the Martian and Artemis, but still very readableI recommend reading Its a bit too long though05-11-2144.91823793PeterGood book, similar to the Martian, but not quitehttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,416-46.6038430.6543875.907375e-010.3739613.530099e-023.152224e-193.152224e-19
Review_TextPosted_DateRatingAverage_RatingNum_of_RatingsHelpfulnessReviewerReview TitleLinkRating_DistributionRating_of_PerformanceRating_of_StorydepthbreadthTopic_1Topic_2Topic_3Topic_4Topic_5
100080Its a great story with a comedy twist, if you like ironic humor this novel will be a great read09-11-1854.6551450Kennethgreat novelhttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-44.2096081.4259467.163825e-201.605594e-016.063995e-017.163825e-202.330411e-01
100081Often found myself relistening to parts just because they were so funny I will be moving to the next book in the series and hope the humor keeps up07-05-1854.6551450Kainin MinceyLoved ithttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-13.2506000.8957368.019996e-017.234487e-023.506236e-023.405489e-025.653828e-02
100082Ive read Hitchhikers Guide before, wayyyyy back in high school Reading it again after so long away was amazing, and Stephen Frys narrator added a whole new facet to the book that I really loved Can we talk about how Douglas Adams description of Zaphods runterm as President of the Galaxy is all too prescient in the era of Trump Because I was getting chillsFunny Space SoBritish Tagsgiving Sweepstakes11-12-1854.6551450KaitlinStephen Fry Makes Ithttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-10.3020980.8545661.792194e-015.438006e-026.226606e-033.362495e-014.239245e-01
100083Great book and narrator It was a fun listen I wish all the books in the series were in one audiobook05-15-1854.6551450Aney1988Very enjoyablehttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-26.9823351.2281961.874276e-018.956039e-205.430550e-012.716463e-022.423528e-01
100084I mostly stick to NonFiction, but I decided to leave my comfort zone and check out this story The storytelling style is really fun, and the voiceover actor performs it in the perfect style The story itself is a crazy SciFi tale about this guy who goes all across the universe and is put in some wild situations Nonetheless the whole novel has some interesting food for thought that raises some neat philosophical ideas Id recommend Audible 20 Review Sweepstakes Entry11-14-1744.6551450KennethSciFi Comedy with some Philosophyhttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-14.0308340.7853898.293918e-028.407249e-011.231855e-022.557594e-036.145975e-02
100085This rendition is delicious If you have never read this book, listen to this audible book instead of reading it Its absolutely wonderful02-09-0954.6551450ElenaIts a classichttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-27.2071530.7770654.080122e-011.048390e-194.933560e-028.061760e-024.620346e-01
100086Stephen Fry is a master Enjoyed hearing him bring this amazing book to life Wonderful05-12-1854.6551450ColleenLove this bookhttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-29.0003530.3896525.346885e-013.494436e-012.799538e-194.947821e-026.638972e-02
100087narrator was absolutely perfect for such a good story everything I expected and more thank you04-27-1854.6551450Brandon ToppinsSci fi so goodhttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-46.0512961.0636501.695819e-197.767011e-012.866638e-021.946326e-011.695819e-19
100088This is the kind of book that allows your imagination to fully participate in the magic of the book while the jokescommentarysatire keep you laughing and awake for long stretches of road Kept us occupied on an allnight drive from Mexico to Colorado10-02-1054.6551450BillPerfect book for a road triphttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-81.6194381.8907351.000000e+004.163306e-194.163306e-194.163306e-194.163306e-19
100089Its been great revisiting this book Ive read it a few times already, but this was my first delve into the audiobook version Stephen Fry did a great job reading and placing the correct timing for the very British humour of the book10-25-1854.6551450James EdgeStill Holds Uphttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,594-44.0239141.2415891.885315e-016.791326e-204.916378e-016.791326e-203.198306e-01